Okan Mert Katipoğlu

Erzincan University · Civil engineering

The study aims to reveal which mother wavelet type performs best in evaporation prediction. This study used a hybrid algorithm that combined K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost) methods, and discrete wavelet transform to estimate the evaporation values in the summer months in Bursa. While establishing wavelet-machine learn...

The amount of sediment load (SL) is important for determining the service life of the downstream dam, river hydraulics, waterworks construction, and reservoir management. The importance of Artificial Intelligence (AI) and nature-based optimization algorithms is increasing in solving water resources problems, such as SL estimation. This study combin...

Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging due to the lack of information on model...

Preventing plunge pool scouring in hydraulic structures is crucial in hydraulic engineering. Although many studies have been conducted experimentally to determine relationship between the scour depth and water jets in several fields, available equations have deficiencies in calculating the exact scour due to complexity of the scour process. This st...

The current research intends to compare the agreement level between the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI), the former’s variant, at different timescales such as 1, 3, 6, 9, 12, and 24 months. This data was compiled from the Mekerra basin with the help of time series of rainfall and...

Flood routing calculations are of vital importance in estimating the floods occurring in the downstream region and taking all necessary measures to minimize the damages that the flood may cause. The prediction success of the created algorithms in the flood routing analysis was tried to be measured by training the daily flood data with machine learn...

Modeling stream flows is vital for water resource planning and flood and drought management. In this study, the performance of hybrid models constructed by combining least square support vector machines (LSSVM), empirical model decomposition (EMD), and particle swarm optimization (PSO) methods in modeling monthly streamflow was evaluated. For estab...

The prediction of hydrological drought is significant for the management of water resources, planning of hydroelectricity production, agricultural production, habitat, and life of living things. The primary aim of this study is to increase the prediction success hydrological drought in the Wadi Ouahrane basin (270 km2). For this purpose, support ve...

Precipitation is a major component of the water cycle. Accurate and reliable estimation of precipitation is essential for various applications. Generally, there are three main types of precipitation products: satellite based, reanalysis, and ground measurements from rain gauge stations. Each type has its advantages and disadvantages. Recent efforts...

In water resources engineering, streamflow estimation models are of great importance. The use of black box models in determining streamflow estimation is preferred because it saves time compared to deterministic models. In addition, the data needed is less in quality and quantity and has a lower transaction volume. Therefore, accurate flow estimati...

Recent meteorological, hydrological, and agricultural droughts in the Mediterranean regions have raised concerns about the impact of climate change. In this study, the meteorological, agricultural, and hydrological droughts were modeled in the Wadi Ouahrane Basin using various machine learning (ML) models and standardized indices of rainfall, evapo...

Revealing the dynamic link between rainfall and runoff, which are the main components of the hydrological cycle, is significant for the planning and managing water resources, disaster risk management, and construction of water structures. This study used feed-forward neural network (FFNN), adaptive neuro-fuzzy inference system (ANFIS), and long sho...

Streamflow estimation is important in hydrology, especially in drought and flood-prone areas. Accurate estimation of streamflow values is crucial for the sustainable management of water resources, the development of early warning systems for disasters, and for various applications such as irrigation, hydropower production, dam sizing, and siltation...

Accurate and reliable flow estimations are of great importance for hydroelectric power generation, flood and drought risk management, and the effective use of water resources. This research carries out a comprehensive study on the application of gated recurrent unit (GRU) neural network, recurrent neural network (RNN), and long short-term memory (L...

Determining drought indices and characteristics in Algeria is crucial because droughts significantly impact water resources and agricultural production. Additionally, identifying the most suitable drought indicator for the region facilitates effective monitoring of droughts. The study’s main objective is to compare hydro-meteorological droughts, de...

Hotter and drier weather conditions due to climate change negatively affect water resources and agricultural production. For this reason, it is vital to analyze the change in potential evapotranspiration (PET) values, which is one of the most important parameters related to plant growth and agricultural irrigation planning. This study analyses the...

This study investigates possible rainfall and drought trends using data from 38 rainfall stations in the Medjerda basin (northeast of Algeria) over 54 years (1965–2018). Drought-related data were calculated with the Standardized precipitation index (SPI). The Mann–Kendall test was used to fnd positive or negative precipitation trends. The magnitud...

Accurate estimation of wind speed (WS) data, which greatly influences meteorological parameters, plays a vital role in the safe operation and optimization of the power system and water resource management. The study’s main aim is to combine artificial intelligence and signal decomposition techniques to improve WS prediction accuracy. Feed-forward b...

Predicting groundwater level (GWL) fluctuations, which act as a reserve water reservoir, Particularly in arid and semi-arid climates, is vital in water resources management and planning. Within the scope of current research, a novel hybrid algorithm is proposed for estimating GWL values in the Tabriz plain of Iran by combining the artificial neural...

Floods are among the most costly natural disasters worldwide. Flood control, one of the important engineering problems, can be solved by modeling floods correctly. Furthermore, flood routing is vital in helping reduce floods' impact on people and communities by allowing timely and appropriate responses. In this study, the empirical mode decompositi...

Solar radiation forecasting is of great importance in generating electricity from solar panels, growing and developing crops, establishing local weather models, and making climate forecasts. In this study, the least square-support vector machine (LS-SVM) with particle swarm optimization (PSO) and variational mode decomposition (VMD) techniques was...

Hidroloji döngüsünün temel bileşenlerinden biri olan buharlaşma, farklı iklim bölgelerindeki çeşitli meteorolojik değişkenlerden farklı şekilde etkilenir. Buharlaşmanun doğru bir şekilde tahmin edilmesi su kaynaklarının yönetimi, sürdürülebilir tarım, sulama sistemlerinin yönetiminde ve su yapısı tasarımı açısından hayati öneme sahiptir. Gelişen ya...

Streamflow modeling is important in water resources management, flood and drought analysis, hydroelectric energy production and agricultural production in arid and semi-arid basins. In this study, feed-forward neural networks (FFNN) and adaptive neuro-fuzzy inference systems (ANFIS) were used to evaluate the effect of various meteorological data on...

Today, the biggest issue appears to be the increase in drought in some regions brought on by global warming, which has greatly increased the significance of water management. In light of evaporation's effect on drought, this research intends to evaluate the effectiveness of hybrid machine learning (ML) models, such as the Gradient Boosting Machines...

Flood routing models are vital in predicting floods and taking all necessary precautions in the region where floods occur, preventing loss of life and property in the region and protecting agricultural areas. This study aims to compare the performance of various machine learning models such as Bagged Tree, Gradient-Boosted Machine, Random Forest, K...

This study aimed to predict monthly flows using an adaptive neuro-fuzzy inference system (ANFIS) and wavelet-ANFIS (W-ANFIS) and to determine the effect of wavelet transformation on the success of the machine learning model. For this purpose, the model inputs are divided into three subcomponents with Daubechies 10 mother wavelets. Subcomponents wit...

With the effect of global warming, the frequency of floods, one of the most important natural disasters, increases, and this increases the damage it causes to people and the environment. Flood routing models play an important role in predicting floods so that all necessary precautions are taken before floods reach the region, loss of life and prope...

Accurate prediction of evapotranspiration values is important in planning agricultural irrigation, crop growth research, and hydrological modeling. This study is aimed at estimating monthly evapotranspiration (ET) values in Hakkâri province by combining support vector regression, bagged tree, and boosted tree methods with wavelet transform. For thi...

In this study, Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Random Forest (RF), Bagged Trees (BT), and Custom Deep Learning methods were used to estimate the potential evapotranspiration (PET) values at Diyarbakir airport station in the Tigris basin. In establishing the models, the average temperature, maximum temperature,...

The prediction of hydrological droughts is vital for surface and ground waters, reservoir levels, hydroelectric power generation, agricultural production, forest fires, climate change, and the survival of living things. This study aimed to forecast 1-month lead-time hydrological droughts in the Yesilirmak basin. For this purpose, support vector reg...

Accurate estimation of streamflow has an important role in water resources management, disaster preparedness and early warning, reservoir operation, and sizing of water structures. In this study, Extreme gradient boosting (XGBoost) and K-Nearest Neighbours (KNN) algorithms are used for the estimation of streamflow. In order to reveal the appropriat...

Due to climate change and increasing demand for water, effective planning of water resources is a current issue. Reliable and accurate streamflow prediction is of great importance in the planning of water resources. This study aimed to predict monthly streamflows in Amasya by combining a discrete wavelet transform and a feedforward backpropagation...

Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of ma...

Determining the trend in meteorological variables is vital in water resources planning, energy production, and the design of water structures. This study analyzed trends and years of change in seasonal and annual average, maximum, minimum temperature, maximum precipitation, average relative humidity, average wind speed, and sunshine duration values...

This study aims to estimate streamflow values with artificial neural networks (ANN) using various meteorological parameters. In developing the ANN model, various combinations of precipitation, air temperatures, and potential evapotranspiration values were used as inputs, and streamflow values were obtained. Meteorological data is divided into 70% t...

Determining trends in potential evapotranspiration (PET) values is of great importance in climate change and drought management, more efficient management of agricultural water resources, and optimal design of irrigation planning. This study carried trend analyses of seasonal and annual PET values calculated between 1964 and 2017 for Batman, Cizre,...

The main purpose of this study is to map the spatio-temporal variation of hydrological drought severities in the Euphrates Basin by using Kriging, Radial Based Function (RBF), Inverse Distance Weighting (IDW), Local Polynomial Interpolation (LPI), and Global Polynomial Interpolation (GPI) methods and to determine the distribution of hydrological dr...

This study analyzes the spatial and temporal distribution of trends on monthly, seasonal, and annual mean temperatures (1967–2017) at 22 stations in the Euphrates Basin of Turkey. The recently proposed innovative trend analysis (ITA) and the nonparametric Mann–Kendall (MK) and Spearman’s rho (SR) test at 5% and 1% significance levels were applied t...

It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. This study aimed to reveal the spatial distribution of seasonal, long-term average precipitation in the Euphrates Basin with various interpolation methods. For this reaso...

In this study, it was aimed to determine the meteorological drought trends in the Euphrates Basin by using rainfall-based Standardised Precipitation Index (SPI), Statistical Z Score Index (ZSI), Rainfall Anomaly Index (RAI) and rainfall and temperature-based Standardised Precipitation Evapotranspiration Index (SPEI) and Reconnaissance Drought Index...

Temperature data is one of the basic inputs of meteorological, hydrological and climatic studies. The completeness of this data is of great importance for reliability in research. This study aimed to compare the performances of various machine learning methods such as support vector machines (SVM), adaptive neuro-fuzzy inference system (ANFIS) and...

It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. In this study, it was aimed to reveal the spatial distribution of seasonal long-term average precipitation in the Euphrates Basin by using various interpolation methods....

Kuraklık hidroelektrik enerji üretimi, sağlık, sanayi, turizm, ekonomi, tarım ve hayvancılık gibi çeşitli sektörleri olumsuz etkileyen bir doğal afettir. Bu nedenle izlenmesi, zamansal ve mekânsal dağılımının belirlenmesi ve önlemler alınarak kuraklık risklerinin yönetilmesi büyük öneme sahiptir. Bu çalışmada, Fırat Havzası’ndaki çeşitli meteoroloj...

In this study, the aim was to measure changes in the spatio-temporal distribution of a potential drought hazard area and determine the risk status of various meteorological and hydrological droughts by using the kriging, radial basis function (RBF), and inverse distance weighting (IDW) interpolation methods. With that goal, in monthly, three-month,...

In this study, the Reconnaissance Drought Index (RDI) values of 16 meteorology observation stations in the Euphrates basin were calculated over a 12-month period, the frequencies of the drought classes were determined, and the index values were subjected to runs analysis to determine the maximum and average drought characteristics (drought duration...

Defined as the global increase in temperatures and changes in precipitation, climate change is regarded as one of the most serious problems of today. It is important to investigate the changes in climate data to increase the reliability and quality of the data used in hydrological studies. In this study, four absolute homogeneity tests were perform...

Drought incidents occur due to the fact that precipitation values are below average for many years. Drought causes serious effects in many sectors, such as agriculture, economy, health, and energy. Therefore, the determination of drought and water scarcity, monitoring, management, and planning of drought and taking early measures are important issu...

Sera gazlarının atmosferdeki salınımının hızla artması küresel ve bölgesel ölçekte ikliminin daha sıcak ve değişken seyir izlemesine neden olmaktadır. Bu nedenle ekstrem (uç) hava ve iklim olaylarının karakteristiklerinde büyük değişimler meydana gelmektedir. Bu doğrultuda meteoroloji tabanlı taşkın ve kuraklık gibi doğal afetlerin önemi git gide a...

Homojen iklim serisi, yalnızca iklim değişikliklerinden etkilenen veri kümeleri olarak tanımlanmaktadır. Verilerin homojen olması uygulanan meteorolojik veya hidrolojik bir modelin doğruluğu ve güvenilirliğini artırmaktadır. Çalışmada kullanılan istasyon verilerinde, ölçüm yönteminin değişmesi, çevresel nedenler ve ölçüm aracından kaynaklanan hatal...

Hidrolojik, meteorolojik ve iklimsel çalışmaların en doğru şekilde değerlendirilebilmesi için verilerin verilerin güvenilir olması gerekir. Bu nedenle, yağış, sıcaklık, buharlaşma, vb. parametrelerin kullanıldığı meteorolojik bir çalışmaya başlamadan önce ön inceleme aşaması olan homojenlik testi gerekmektedir. Homojenlik testi sonucunda verilerde...

Havza karakteristiklerinin belirlenmesi, Coğrafi Bilgi Sistemi (CBS) ortamında hidrolojik analiz, su kaynakları yönetimi, taşkın ve kuraklık risk modellemesi, hidrolojik modeller ve bu modellerle ilgili taşkın modelleri, su kirleticileri taşıma modelleri, su kalitesi modelleri ve su temini modelleri gibi uygulama alanları için önemli ve gereklidir....

Kuraklık, uzun bir süre boyunca yağış eksikliğinden kaynaklanan bir meteorolojik olay olarak ifade edilir. Kuraklık, kapladığı alan, uzun vadeli etkileri ve birçok sektör üzenindeki olumsuz etkileri nedeniyle büyük önem taşıyan doğal afetlerden biridir. Kuraklık olaylarını doğru bir şekilde izlemek ve karakteristiklerini (kuraklık süre, şiddet, baş...

Kuraklık uzun süreli su eksikliği sonucunda ortaya çıkan ve hidroelektrik üretimi, su kaynakları, sağlık, sanayi, turizm, toplum, tarım ve hayvancılık gibi çeşitli sektörleri olumsuz etkileyen bir doğal afettir. Bu doğal afet, hidrolojik döngünün farklı aşamalarında meydana gelen olaylardan kaynaklanmaktadır ve genellikle meteorolojik, tarımsal, hi...

Determining the characteristics and classes of drought is of great importance in investigating the effects of drought. In this study, the frequencies of drought classes were determined by using 1-month, 3-month and 12-month SPEI values, between 1966 and 2017 in Erzincan precipitation observation station. In addition, maximum and average drought cha...

Keywords: The goodness of fit test, Hydrological droughts, Run analysis, Standardized Runoff index (SRI) Streamflow. Abstract Drought is one of the dangerous natural disasters that have great socioeconomic effects and are difficult to prevent. Therefore, the analysis of droughts is of vital importance. In this study, 1-month, 3-month and 12-month,...

The scarcity of water and major water demands cause that droughts give rise to important economic, social and environmental results. For this reason, drought periods must be determined beforehand and must be controlled. In this study, stochastic models were developed in order to estimate monthly flow rates of the Karasu River. The best-fitting mode...